Overview

Brought to you by YData

Dataset statistics

Number of variables20
Number of observations750000
Missing cells233124
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.4 MiB
Average record size in memory90.0 B

Variable types

Numeric8
Categorical2
Boolean10

Alerts

Episode_Length_minutes is highly overall correlated with Listening_Time_minutesHigh correlation
Genre_Business is highly overall correlated with Podcast_NameHigh correlation
Genre_Music is highly overall correlated with Podcast_NameHigh correlation
Genre_True Crime is highly overall correlated with Podcast_NameHigh correlation
Listening_Time_minutes is highly overall correlated with Episode_Length_minutesHigh correlation
Podcast_Name is highly overall correlated with Genre_Business and 2 other fieldsHigh correlation
Genre_Business is highly imbalanced (50.8%) Imbalance
Genre_Comedy is highly imbalanced (50.4%) Imbalance
Genre_Education is highly imbalanced (65.1%) Imbalance
Genre_Health is highly imbalanced (54.6%) Imbalance
Genre_Lifestyle is highly imbalanced (50.0%) Imbalance
Genre_Music is highly imbalanced (58.5%) Imbalance
Genre_News is highly imbalanced (58.2%) Imbalance
Episode_Length_minutes has 87093 (11.6%) missing values Missing
Guest_Popularity_percentage has 146030 (19.5%) missing values Missing
Podcast_Name has 17327 (2.3%) zeros Zeros
Publication_Day has 108237 (14.4%) zeros Zeros
Number_of_Ads has 217592 (29.0%) zeros Zeros
Listening_Time_minutes has 8551 (1.1%) zeros Zeros

Reproduction

Analysis started2025-04-24 11:49:18.432688
Analysis finished2025-04-24 11:49:58.649863
Duration40.22 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Podcast_Name
Real number (ℝ)

High correlation  Zeros 

Distinct48
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.515731
Minimum0
Maximum47
Zeros17327
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:49:58.913785image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median23
Q337
95-th percentile45
Maximum47
Range47
Interquartile range (IQR)26

Descriptive statistics

Standard deviation14.137577
Coefficient of variation (CV)0.60119657
Kurtosis-1.2686177
Mean23.515731
Median Absolute Deviation (MAD)13
Skewness0.015133322
Sum17636798
Variance199.87108
MonotonicityNot monotonic
2025-04-24T20:49:59.307239image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
42 22847
 
3.0%
39 20053
 
2.7%
15 19635
 
2.6%
43 19549
 
2.6%
14 19488
 
2.6%
3 19480
 
2.6%
41 19364
 
2.6%
17 19272
 
2.6%
30 18889
 
2.5%
6 17735
 
2.4%
Other values (38) 553688
73.8%
ValueCountFrequency (%)
0 17327
2.3%
1 11543
1.5%
2 17012
2.3%
3 19480
2.6%
4 15927
2.1%
5 17374
2.3%
6 17735
2.4%
7 13138
1.8%
8 13391
1.8%
9 17452
2.3%
ValueCountFrequency (%)
47 14043
1.9%
46 15009
2.0%
45 17254
2.3%
44 16373
2.2%
43 19549
2.6%
42 22847
3.0%
41 19364
2.6%
40 13053
1.7%
39 20053
2.7%
38 16191
2.2%

Episode_Title
Real number (ℝ)

Distinct100
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.445811
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:49:59.719447image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q128
median52
Q375
95-th percentile95
Maximum100
Range99
Interquartile range (IQR)47

Descriptive statistics

Standard deviation28.085623
Coefficient of variation (CV)0.54592633
Kurtosis-1.1612279
Mean51.445811
Median Absolute Deviation (MAD)24
Skewness-0.061889975
Sum38584358
Variance788.8022
MonotonicityNot monotonic
2025-04-24T20:50:00.130775image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71 10515
 
1.4%
62 10373
 
1.4%
31 10292
 
1.4%
61 9991
 
1.3%
69 9864
 
1.3%
23 9762
 
1.3%
63 9743
 
1.3%
81 9741
 
1.3%
64 9686
 
1.3%
72 9554
 
1.3%
Other values (90) 650479
86.7%
ValueCountFrequency (%)
1 5922
0.8%
2 5134
0.7%
3 6943
0.9%
4 7000
0.9%
5 6366
0.8%
6 6993
0.9%
7 6369
0.8%
8 7690
1.0%
9 6751
0.9%
10 6454
0.9%
ValueCountFrequency (%)
100 6348
0.8%
99 9270
1.2%
98 5902
0.8%
97 6521
0.9%
96 6720
0.9%
95 4838
0.6%
94 6763
0.9%
93 5919
0.8%
92 6533
0.9%
91 6975
0.9%

Episode_Length_minutes
Real number (ℝ)

High correlation  Missing 

Distinct12268
Distinct (%)1.9%
Missing87093
Missing (%)11.6%
Infinite0
Infinite (%)0.0%
Mean64.504738
Minimum0
Maximum325.24
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:50:00.532793image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.68
Q135.73
median63.84
Q394.07
95-th percentile115.29
Maximum325.24
Range325.24
Interquartile range (IQR)58.34

Descriptive statistics

Standard deviation32.969603
Coefficient of variation (CV)0.51111909
Kurtosis-1.2030327
Mean64.504738
Median Absolute Deviation (MAD)29.16
Skewness-0.0020056126
Sum42760643
Variance1086.9947
MonotonicityNot monotonic
2025-04-24T20:50:00.944504image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 925
 
0.1%
34.4 617
 
0.1%
30.69 576
 
0.1%
31.68 533
 
0.1%
31.46 491
 
0.1%
47.02 461
 
0.1%
29.61 448
 
0.1%
106.52 426
 
0.1%
111.68 420
 
0.1%
114.98 411
 
0.1%
Other values (12258) 657599
87.7%
(Missing) 87093
 
11.6%
ValueCountFrequency (%)
0 1
 
< 0.1%
1.24 1
 
< 0.1%
1.48 1
 
< 0.1%
1.84 1
 
< 0.1%
2.47 4
 
< 0.1%
2.97 1
 
< 0.1%
5 38
< 0.1%
5.0000636 1
 
< 0.1%
5.00006409 6
 
< 0.1%
5.00006607 1
 
< 0.1%
ValueCountFrequency (%)
325.24 1
 
< 0.1%
120.93 1
 
< 0.1%
120.73 1
 
< 0.1%
120.64 2
 
< 0.1%
120.37 2
 
< 0.1%
120.32 1
 
< 0.1%
120.06 1
 
< 0.1%
119.99 7
 
< 0.1%
119.98 55
< 0.1%
119.97 44
< 0.1%
Distinct8038
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.859901
Minimum1.3
Maximum119.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:50:01.360912image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1.3
5-th percentile24.79
Q139.41
median60.05
Q379.53
95-th percentile95.77
Maximum119.46
Range118.16
Interquartile range (IQR)40.12

Descriptive statistics

Standard deviation22.873098
Coefficient of variation (CV)0.38211052
Kurtosis-1.2067021
Mean59.859901
Median Absolute Deviation (MAD)20.04
Skewness0.0049262753
Sum44894926
Variance523.17859
MonotonicityNot monotonic
2025-04-24T20:50:01.789641image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.68 560
 
0.1%
26.72 523
 
0.1%
56.29 490
 
0.1%
30.14 445
 
0.1%
31.57 439
 
0.1%
58.71 431
 
0.1%
80.43 428
 
0.1%
67.54 411
 
0.1%
36.79 410
 
0.1%
67.19 401
 
0.1%
Other values (8028) 745462
99.4%
ValueCountFrequency (%)
1.3 1
 
< 0.1%
1.47 1
 
< 0.1%
1.73 1
 
< 0.1%
1.77 2
 
< 0.1%
1.89 2
 
< 0.1%
2.95 2
 
< 0.1%
20 18
 
< 0.1%
20.01 69
< 0.1%
20.02 42
< 0.1%
20.03 62
< 0.1%
ValueCountFrequency (%)
119.46 1
 
< 0.1%
118.93 1
 
< 0.1%
118.73 1
 
< 0.1%
118.69 1
 
< 0.1%
117.76 2
 
< 0.1%
117.14 5
< 0.1%
115.18 1
 
< 0.1%
114.97 1
 
< 0.1%
114.73 1
 
< 0.1%
112.44 1
 
< 0.1%

Publication_Day
Real number (ℝ)

Zeros 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.962776
Minimum0
Maximum6
Zeros108237
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:50:02.126773image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.9973986
Coefficient of variation (CV)0.67416456
Kurtosis-1.2339942
Mean2.962776
Median Absolute Deviation (MAD)2
Skewness0.035920341
Sum2222082
Variance3.989601
MonotonicityNot monotonic
2025-04-24T20:50:02.422043image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 115946
15.5%
1 111963
14.9%
0 108237
14.4%
6 107886
14.4%
4 104360
13.9%
2 103505
13.8%
5 98103
13.1%
ValueCountFrequency (%)
0 108237
14.4%
1 111963
14.9%
2 103505
13.8%
3 115946
15.5%
4 104360
13.9%
5 98103
13.1%
6 107886
14.4%
ValueCountFrequency (%)
6 107886
14.4%
5 98103
13.1%
4 104360
13.9%
3 115946
15.5%
2 103505
13.8%
1 111963
14.9%
0 108237
14.4%

Publication_Time
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.8 MiB
3
196849 
1
195778 
0
179460 
2
177913 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters750000
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row0
3rd row1
4th row2
5th row0

Common Values

ValueCountFrequency (%)
3 196849
26.2%
1 195778
26.1%
0 179460
23.9%
2 177913
23.7%

Length

2025-04-24T20:50:03.137110image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-24T20:50:03.475529image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
3 196849
26.2%
1 195778
26.1%
0 179460
23.9%
2 177913
23.7%

Most occurring characters

ValueCountFrequency (%)
3 196849
26.2%
1 195778
26.1%
0 179460
23.9%
2 177913
23.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 750000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 196849
26.2%
1 195778
26.1%
0 179460
23.9%
2 177913
23.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 750000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 196849
26.2%
1 195778
26.1%
0 179460
23.9%
2 177913
23.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 750000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 196849
26.2%
1 195778
26.1%
0 179460
23.9%
2 177913
23.7%

Guest_Popularity_percentage
Real number (ℝ)

Missing 

Distinct10019
Distinct (%)1.7%
Missing146030
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean52.236449
Minimum0
Maximum119.91
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:50:03.870847image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.79
Q128.38
median53.58
Q376.6
95-th percentile95.1
Maximum119.91
Range119.91
Interquartile range (IQR)48.22

Descriptive statistics

Standard deviation28.451241
Coefficient of variation (CV)0.54466263
Kurtosis-1.1501171
Mean52.236449
Median Absolute Deviation (MAD)24.23
Skewness-0.10703539
Sum31549248
Variance809.47314
MonotonicityNot monotonic
2025-04-24T20:50:04.402880image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68.53 378
 
0.1%
29.7 339
 
< 0.1%
42.69 332
 
< 0.1%
54.59 300
 
< 0.1%
41.29 298
 
< 0.1%
71.4 296
 
< 0.1%
84.57 285
 
< 0.1%
65.16 284
 
< 0.1%
70.99 283
 
< 0.1%
69.72 281
 
< 0.1%
Other values (10009) 600894
80.1%
(Missing) 146030
 
19.5%
ValueCountFrequency (%)
0 3
 
< 0.1%
0.01 47
< 0.1%
0.02 13
 
< 0.1%
0.03 27
 
< 0.1%
0.04 88
< 0.1%
0.05 12
 
< 0.1%
0.06 82
< 0.1%
0.07 86
< 0.1%
0.08 16
 
< 0.1%
0.09 51
< 0.1%
ValueCountFrequency (%)
119.91 1
< 0.1%
115.62 2
< 0.1%
115.43 1
< 0.1%
115.41 1
< 0.1%
114.88 1
< 0.1%
114.72 2
< 0.1%
110.14 1
< 0.1%
107.81 2
< 0.1%
107.58 1
< 0.1%
107.34 1
< 0.1%

Number_of_Ads
Real number (ℝ)

Zeros 

Distinct12
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.3488549
Minimum0
Maximum103.91
Zeros217592
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:50:04.765071image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum103.91
Range103.91
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1511304
Coefficient of variation (CV)0.85341306
Kurtosis505.89391
Mean1.3488549
Median Absolute Deviation (MAD)1
Skewness6.0329918
Sum1011639.8
Variance1.3251012
MonotonicityNot monotonic
2025-04-24T20:50:05.123621image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 217592
29.0%
1 214069
28.5%
3 160173
21.4%
2 158156
21.1%
103.25 2
 
< 0.1%
53.37 1
 
< 0.1%
103.91 1
 
< 0.1%
103 1
 
< 0.1%
53.42 1
 
< 0.1%
103.75 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 217592
29.0%
1 214069
28.5%
2 158156
21.1%
3 160173
21.4%
12 1
 
< 0.1%
53.37 1
 
< 0.1%
53.42 1
 
< 0.1%
103 1
 
< 0.1%
103.25 2
 
< 0.1%
103.75 1
 
< 0.1%
ValueCountFrequency (%)
103.91 1
 
< 0.1%
103.88 1
 
< 0.1%
103.75 1
 
< 0.1%
103.25 2
 
< 0.1%
103 1
 
< 0.1%
53.42 1
 
< 0.1%
53.37 1
 
< 0.1%
12 1
 
< 0.1%
3 160173
21.4%
2 158156
21.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
0
251291 
-1
250116 
1
248593 

Length

Max length2
Median length1
Mean length1.333488
Min length1

Characters and Unicode

Total characters1000116
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row-1
3rd row-1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 251291
33.5%
-1 250116
33.3%
1 248593
33.1%

Length

2025-04-24T20:50:05.487280image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-24T20:50:05.804356image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 498709
66.5%
0 251291
33.5%

Most occurring characters

ValueCountFrequency (%)
1 498709
49.9%
0 251291
25.1%
- 250116
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1000116
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 498709
49.9%
0 251291
25.1%
- 250116
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1000116
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 498709
49.9%
0 251291
25.1%
- 250116
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1000116
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 498709
49.9%
0 251291
25.1%
- 250116
25.0%

Listening_Time_minutes
Real number (ℝ)

High correlation  Zeros 

Distinct42807
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.437406
Minimum0
Maximum119.97
Zeros8551
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size5.7 MiB
2025-04-24T20:50:06.189838image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.07879
Q123.17835
median43.37946
Q364.81158
95-th percentile93.67793
Maximum119.97
Range119.97
Interquartile range (IQR)41.63323

Descriptive statistics

Standard deviation27.138306
Coefficient of variation (CV)0.59726794
Kurtosis-0.66123629
Mean45.437406
Median Absolute Deviation (MAD)20.75602
Skewness0.35081226
Sum34078055
Variance736.48764
MonotonicityNot monotonic
2025-04-24T20:50:06.613250image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8551
 
1.1%
5.82 124
 
< 0.1%
10.55 108
 
< 0.1%
8.75 108
 
< 0.1%
19.71 98
 
< 0.1%
6.16 98
 
< 0.1%
7.92 97
 
< 0.1%
14.93 97
 
< 0.1%
11.91 93
 
< 0.1%
12.78 92
 
< 0.1%
Other values (42797) 740534
98.7%
ValueCountFrequency (%)
0 8551
1.1%
0.00056 7
 
< 0.1%
0.00175 8
 
< 0.1%
0.00661 18
 
< 0.1%
0.0105 7
 
< 0.1%
0.01077 24
 
< 0.1%
0.01257 30
 
< 0.1%
0.0296 15
 
< 0.1%
0.03228 16
 
< 0.1%
0.0343 18
 
< 0.1%
ValueCountFrequency (%)
119.97 22
< 0.1%
119.9 16
< 0.1%
119.8 18
< 0.1%
119.79 14
< 0.1%
119.78 17
< 0.1%
119.74 15
< 0.1%
119.73 14
< 0.1%
119.67 12
< 0.1%
119.66 22
< 0.1%
119.56 17
< 0.1%

Genre_Business
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
669479 
True
80521 
ValueCountFrequency (%)
False 669479
89.3%
True 80521
 
10.7%
2025-04-24T20:50:06.956698image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Genre_Comedy
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
668547 
True
81453 
ValueCountFrequency (%)
False 668547
89.1%
True 81453
 
10.9%
2025-04-24T20:50:07.246211image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Genre_Education
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
700900 
True
 
49100
ValueCountFrequency (%)
False 700900
93.5%
True 49100
 
6.5%
2025-04-24T20:50:07.522382image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Genre_Health
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
678584 
True
71416 
ValueCountFrequency (%)
False 678584
90.5%
True 71416
 
9.5%
2025-04-24T20:50:07.799624image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Genre_Lifestyle
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
667539 
True
82461 
ValueCountFrequency (%)
False 667539
89.0%
True 82461
 
11.0%
2025-04-24T20:50:08.079041image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Genre_Music
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
687257 
True
 
62743
ValueCountFrequency (%)
False 687257
91.6%
True 62743
 
8.4%
2025-04-24T20:50:08.375857image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Genre_News
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
686615 
True
 
63385
ValueCountFrequency (%)
False 686615
91.5%
True 63385
 
8.5%
2025-04-24T20:50:08.647148image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
662394 
True
87606 
ValueCountFrequency (%)
False 662394
88.3%
True 87606
 
11.7%
2025-04-24T20:50:08.918700image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
663744 
True
86256 
ValueCountFrequency (%)
False 663744
88.5%
True 86256
 
11.5%
2025-04-24T20:50:09.212982image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Genre_True Crime
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size732.6 KiB
False
664941 
True
85059 
ValueCountFrequency (%)
False 664941
88.7%
True 85059
 
11.3%
2025-04-24T20:50:09.502174image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Interactions

2025-04-24T20:49:46.691573image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:34.192518image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:35.508013image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:36.998813image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:38.561696image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:40.134538image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:41.587608image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:43.141594image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:47.168354image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:34.353057image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:35.676496image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:37.164186image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:38.754066image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:40.359943image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:41.764258image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:43.312263image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:47.740983image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:34.510666image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:35.860275image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:37.338822image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:38.903011image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:40.561102image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:41.976732image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:43.470127image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:48.264196image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:34.684621image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:36.047413image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:37.515297image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:39.088065image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:40.752474image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:42.159958image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:43.628318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:48.821974image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:34.856962image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:36.223878image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:37.689600image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:39.291481image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:40.957051image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:42.379248image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:44.116851image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:49.295900image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:35.013485image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:36.373179image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:37.877147image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:39.497582image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:41.107021image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:42.547627image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:44.735736image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:49.858864image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:35.179416image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:36.537544image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:38.167997image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:39.710766image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:41.251902image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:42.732980image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:45.309638image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:50.444410image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:35.338289image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:36.835445image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:38.373750image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:39.908055image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:41.416439image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:42.918772image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-04-24T20:49:45.829872image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Correlations

2025-04-24T20:50:09.758871image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Episode_Length_minutesEpisode_SentimentEpisode_TitleGenre_BusinessGenre_ComedyGenre_EducationGenre_HealthGenre_LifestyleGenre_MusicGenre_NewsGenre_SportsGenre_TechnologyGenre_True CrimeGuest_Popularity_percentageHost_Popularity_percentageListening_Time_minutesNumber_of_AdsPodcast_NamePublication_DayPublication_Time
Episode_Length_minutes1.0000.022-0.0200.0060.0140.0060.0080.0050.0140.0050.0140.0120.002-0.0090.0240.932-0.0580.0060.0070.013
Episode_Sentiment0.0221.0000.0100.0020.0030.0040.0040.0080.0030.0100.0010.0080.0090.0130.0140.0370.0020.0120.0090.011
Episode_Title-0.0200.0101.0000.0100.0220.0150.0110.0110.0150.0170.0190.0180.0170.0420.019-0.0220.0060.0060.0030.005
Genre_Business0.0060.0020.0101.0000.1210.0920.1120.1220.1050.1050.1260.1250.1240.0160.0140.0100.0000.5690.0120.006
Genre_Comedy0.0140.0030.0220.1211.0000.0920.1130.1230.1050.1060.1270.1260.1250.0200.0110.0160.0010.4680.0120.006
Genre_Education0.0060.0040.0150.0920.0921.0000.0860.0930.0800.0800.0960.0950.0950.0070.0110.0180.0000.3000.0100.007
Genre_Health0.0080.0040.0110.1120.1130.0861.0000.1140.0980.0990.1180.1170.1160.0120.0140.0150.0010.4260.0110.004
Genre_Lifestyle0.0050.0080.0110.1220.1230.0930.1141.0000.1060.1070.1280.1270.1260.0090.0140.0060.0000.4530.0110.003
Genre_Music0.0140.0030.0150.1050.1050.0800.0980.1061.0000.0920.1100.1090.1080.0050.0090.0140.0040.5100.0040.004
Genre_News0.0050.0100.0170.1050.1060.0800.0990.1070.0921.0000.1100.1100.1090.0130.0100.0130.0000.4130.0060.012
Genre_Sports0.0140.0010.0190.1260.1270.0960.1180.1280.1100.1101.0000.1310.1300.0190.0180.0250.0000.4620.0100.003
Genre_Technology0.0120.0080.0180.1250.1260.0950.1170.1270.1090.1100.1311.0000.1290.0140.0150.0210.0000.3490.0160.003
Genre_True Crime0.0020.0090.0170.1240.1250.0950.1160.1260.1080.1090.1300.1291.0000.0120.0120.0140.0030.6540.0140.008
Guest_Popularity_percentage-0.0090.0130.0420.0160.0200.0070.0120.0090.0050.0130.0190.0140.0121.0000.023-0.0140.009-0.005-0.0000.011
Host_Popularity_percentage0.0240.0140.0190.0140.0110.0110.0140.0140.0090.0100.0180.0150.0120.0231.0000.045-0.017-0.002-0.0040.010
Listening_Time_minutes0.9320.037-0.0220.0100.0160.0180.0150.0060.0140.0130.0250.0210.014-0.0140.0451.000-0.1150.0040.0050.026
Number_of_Ads-0.0580.0020.0060.0000.0010.0000.0010.0000.0040.0000.0000.0000.0030.009-0.017-0.1151.0000.0090.0050.001
Podcast_Name0.0060.0120.0060.5690.4680.3000.4260.4530.5100.4130.4620.3490.654-0.005-0.0020.0040.0091.0000.0030.010
Publication_Day0.0070.0090.0030.0120.0120.0100.0110.0110.0040.0060.0100.0160.014-0.000-0.0040.0050.0050.0031.0000.009
Publication_Time0.0130.0110.0050.0060.0060.0070.0040.0030.0040.0120.0030.0030.0080.0110.0100.0260.0010.0100.0091.000

Missing values

2025-04-24T20:49:50.985527image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-24T20:49:53.421766image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-04-24T20:49:57.593638image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Podcast_NameEpisode_TitleEpisode_Length_minutesHost_Popularity_percentagePublication_DayPublication_TimeGuest_Popularity_percentageNumber_of_AdsEpisode_SentimentListening_Time_minutesGenre_BusinessGenre_ComedyGenre_EducationGenre_HealthGenre_LifestyleGenre_MusicGenre_NewsGenre_SportsGenre_TechnologyGenre_True Crime
03498.0NaN74.8143NaN0.0131.41998FalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
12426.0119.8066.952075.952.0-188.01241FalseTrueFalseFalseFalseFalseFalseFalseFalseFalse
24016.073.9069.97518.970.0-144.92531FalseFalseTrueFalseFalseFalseFalseFalseFalseFalse
31045.067.1757.221278.702.0146.27824FalseFalseFalseFalseFalseFalseFalseFalseTrueFalse
43186.0110.5180.071058.683.0075.61031FalseFalseFalseTrueFalseFalseFalseFalseFalseFalse
51419.026.5448.9620NaN3.0122.77047FalseFalseFalseTrueFalseFalseFalseFalseFalseFalse
6647.069.8335.823339.020.0064.75024FalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
73544.048.5244.994320.120.0122.37517FalseFalseFalseFalseFalseFalseTrueFalseFalseFalse
8832.0105.8769.8111NaN2.0068.00124FalseFalseFalseFalseFalseFalseTrueFalseFalseFalse
93381.0NaN82.184359.723.0045.94761FalseFalseFalseFalseFalseTrueFalseFalseFalseFalse
Podcast_NameEpisode_TitleEpisode_Length_minutesHost_Popularity_percentagePublication_DayPublication_TimeGuest_Popularity_percentageNumber_of_AdsEpisode_SentimentListening_Time_minutesGenre_BusinessGenre_ComedyGenre_EducationGenre_HealthGenre_LifestyleGenre_MusicGenre_NewsGenre_SportsGenre_TechnologyGenre_True Crime
7499901361.0114.7283.623291.800.0061.16847TrueFalseFalseFalseFalseFalseFalseFalseFalseFalse
74999135.062.4630.0350NaN0.0153.32434TrueFalseFalseFalseFalseFalseFalseFalseFalseFalse
7499921275.048.6788.626125.653.0142.08465FalseFalseFalseFalseTrueFalseFalseFalseFalseFalse
7499934183.023.5238.145186.170.0019.71374FalseFalseFalseFalseTrueFalseFalseFalseFalseFalse
7499942567.08.9385.5221NaN1.007.39878FalseTrueFalseFalseFalseFalseFalseFalseFalseFalse
7499952625.075.6669.3622NaN0.0-156.87058FalseFalseTrueFalseFalseFalseFalseFalseFalseFalse
749996221.075.7535.2123NaN2.0045.46242TrueFalseFalseFalseFalseFalseFalseFalseFalseFalse
7499972851.030.9878.584284.890.0-115.26000FalseFalseFalseFalseTrueFalseFalseFalseFalseFalse
7499984147.0108.9845.394293.270.0-1100.72939FalseFalseFalseFalseTrueFalseFalseFalseFalseFalse
7499993899.024.1022.452336.720.0011.94439FalseFalseFalseFalseFalseFalseFalseTrueFalseFalse